SBIR Phase I: A platform to connect underserved and underrepresented communities to science, technology, engineering and mathemetics (STEM) careers

SBIR 第一阶段：一个将服务不足和代表性不足的社区与科学、技术、工程和数学 (STEM) 职业联系起来的平台

• 批准号: 2232689
• 负责人: Gina Coburn
• 金额: $ 27.5万
• 依托单位: NERRATIVE TECHNOLOGY INC.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-15 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2232689&HistoricalAwards=false
• 关键词: SBIR; Phase; platform; connect; underserved

The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is in providing more access to educational pathways, and equitable opportunities for learning, professional development, and career growth to marginalized student communities. The project proposes the development and implementation of a digital human element to meet the needs of these impacted individuals. The project is not such organizations, but also to create pathways to equitable opportunities for those coming from marginalized communities to participate in some of the most innovative learning modalities, while studying for some of the most promising STEM careers. The intellectual merit of this project lies in the use of big data and machine learning in personality and skills measurement. The artificial intelligence algorithms will be juxtaposed onto game mechanics to facilitate ease of use due to the familiarity with other existing user interfaces. The interface has a complex and dynamic personality profiling engine. The research will deliver standards and methodologies, evaluate existing exchange formats, improve accuracy metrics for neural networks, and deliver an initial digital human prototype. The technology will create a Data Lake containing professions, skills, certificate requirements, social media profiles, resumes, recorded interviews, and other online activities that are shared by the users for establishing personalized, artificial intelligence (AI)-supported career growth profiles. Information in the Data Lake will be curated to facilitate the development of personalized career development strategies. A Delta Lake model will be used to continuously stream data with improved data quality to drive the personalization requirements of both the digital human and the user.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这项小型企业创新研究（SBIR）I阶段项目的更广泛/商业影响在于为边缘化的学生社区提供更多获得教育途径，学习，专业发展和职业增长的公平机会。该项目提议开发和实施数字人类因素，以满足这些受影响个人的需求。该项目不是这样的组织，而是为来自边缘化社区的人创造公平机会的途径，以参与一些最具创新性的学习方式，同时研究一些最有前途的STEM职业。该项目的智力优点在于在人格和技能测量中使用大数据和机器学习。由于熟悉其他现有用户界面，人工智能算法将并列在游戏机制上，以促进易用性。 该界面具有复杂且动态的个性分析引擎。该研究将提供标准和方法论，评估现有的交换格式，提高神经网络的准确度指标，并提供初始的数字人类原型。该技术将创建一个数据湖，其中包含专业，技能，证书要求，社交媒体概况，简历，记录的访谈和其他在线活动，这些活动由用户共享，这些活动是为建立个性化的，人工智能（AI）支持的职业增长概况而共享的。数据湖中的信息将被策划，以促进个性化职业发展策略的发展。 Delta Lake模型将用于以改进的数据质量来连续流数据，以推动数字人和用户的个性化要求。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子的评估和更广泛的影响来通过评估来获得支持的。